scholarly journals Model-Based Approach to Engineering Resilience in Multi-UAV Systems

Systems ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 11 ◽  
Author(s):  
Edwin Ordoukhanian ◽  
Azad Madni
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Research Community ◽  
Operational Environment ◽  
System Operation ◽  
Aerial Vehicles ◽  
Simulation Based ◽  
Simulation Results ◽  
Time Evaluation ◽  
Context Simulation ◽  
Multi Uav

Multi-UAV Operations are an area of great interest in government, industry, and research community. In multi-UAV operations, a group of unmanned aerial vehicles (UAVs) are deployed to carry out missions such as search and rescue or disaster relief. As multi-UAV systems operate in an open operational environment, many disrupting events can occur. To this end, resilience of these systems is of great importance. The research performed and reported in this paper utilizes simulation-based research methodology and demonstrates that resilience of multi-UAV systems can be achieved by real-time evaluation of resilience alternatives during system operation. This evaluation is done using a dynamic utility function where priorities change as a function of context. Simulation results show that resilience response can in fact change depending on the context.

scholarly journals Cooperative Attack-Defense Decision-Making of Multi-UAV Using Satisficing Decision-Enhanced Wolf Pack Search Algorithm

2021 ◽  
Author(s):  
Tongle Zhou ◽  
Mou Chen ◽  
Yuhui Wang ◽  
Ronggang Zhu ◽  
Chenguang Yang
Keyword(s):  
Decision Making ◽  
Unmanned Aerial Vehicles ◽  
Decision Problem ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Target Information ◽  
Aerial Vehicles ◽  
Air Combat ◽  
Simulation Results ◽  
Multi Uav

Abstract Unmanned Aerial Vehicles (UAVs) have shown their superiority for applications in complicated military missions. A cooperative attack-defense decision-making method based on satisficing decision-enhanced wolf pack search (SDEWPS) algorithm is developed for multi-UAV air combat in this paper. Firstly, the multi-UAV air combat mathematical model is provided and the attack-defense decision-making constraints are defined. Besides the traditional air combat situation, the capability of UAVs and target information including target type and target intention are all considered in this paper to establish the air combat superiority function. Then, the wolf pack search (WPS) algorithm is used to solve the attack decision problem. In order to improve efficiency, the satisficing decision theory is employed to enhance the WPS to obtain the satisficing solution rather than optimal solution. The simulation results show that the developed method can realize the cooperative attack decision-making.

Intelligent cooperative collision avoidance via fuzzy potential fields

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Potential Fields ◽  
Rule Base ◽  
Local Minima ◽  
Inference System ◽  
Aerial Vehicles ◽  
Different Shapes ◽  
Simulation Results

Summary This paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.

scholarly journals Distributed Cooperative Avoidance Control for Multi-Unmanned Aerial Vehicles

Actuators ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Sunan Huang ◽  
Rodney Swee Huat Teo ◽  
Wenqi Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Case Studies ◽  
Collision Avoidance ◽  
Hardware In The Loop ◽  
Crucial Issue ◽  
Communication Failure ◽  
Aerial Vehicles ◽  
Avoidance Control ◽  
Velocity Obstacle ◽  
Multi Uav

It is well-known that collision-free control is a crucial issue in the path planning of unmanned aerial vehicles (UAVs). In this paper, we explore the collision avoidance scheme in a multi-UAV system. The research is based on the concept of multi-UAV cooperation combined with information fusion. Utilizing the fused information, the velocity obstacle method is adopted to design a decentralized collision avoidance algorithm. Four case studies are presented for the demonstration of the effectiveness of the proposed method. The first two case studies are to verify if UAVs can avoid a static circular or polygonal shape obstacle. The third case is to verify if a UAV can handle a temporary communication failure. The fourth case is to verify if UAVs can avoid other moving UAVs and static obstacles. Finally, hardware-in-the-loop test is given to further illustrate the effectiveness of the proposed method.

Forest Firefighting Monitoring System Based on UAV Team and Remote Sensing

2019 ◽  
pp. 220-241
Author(s):  
Maryna Zharikova ◽  
Vladimir Sherstjuk
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Fire Response ◽  
Ground Support ◽  
Aerial Vehicles ◽  
Remote Sensing Techniques ◽  
Fire Spreading ◽  
Multi Uav

In this chapter, the authors propose an approach to using a heterogeneous team of unmanned aerial vehicles and remote sensing techniques to perform tactical forest firefighting operations. The authors present the three-level architecture of the multi-UAV-based forest firefighting monitoring system; features of patrolling, confirming, and monitoring missions; as well as functions of UAV in such missions. The authors consider an infrastructure for the UAV ground support and equipment used for the UAVs control. The method of the data integration into a fire-spreading model in a real-time DSS for the forest fire response is proposed. The proposed approach has been tested with the multi-UAV team that included three drones for the patrol missions, one helicopter for the confirmation mission, and one octocopter for the monitoring mission. The performance of such multi-UAV team has been studied in the laboratory conditions. The result of the experiment has shown that the proposed approach provides required credibility and efficiency of fire prediction and response.

Multi-UAV Specification and Control with a Single Pilot-in-the-Loop

2020 ◽  
Vol 08 (04) ◽  
pp. 269-277
Author(s):  
Patricio Moreno ◽  
Santiago Esteva ◽  
Ignacio Mas ◽  
Juan I. Giribet
Keyword(s):  
Remote Control ◽  
Unmanned Aerial Vehicles ◽  
Field Experiments ◽  
Aerial Vehicles ◽  
Simulated Environment ◽  
Aerial Vehicle ◽  
Space Formulation ◽  
Trajectory Following ◽  
And Control ◽  
Multi Uav

This work presents a multi-unmanned aerial vehicle formation implementing a trajectory-following controller based on the cluster-space robot coordination method. The controller is augmented with a feed-forward input from a control station operator. This teleoperation input is generated by means of a remote control, as a simple way of modifying the trajectory or taking over control of the formation during flight. The cluster-space formulation presents a simple specification of the system’s motion and, in this work, the operator benefits from this capability to easily evade obstacles by means of controlling the cluster parameters in real time. The proposed augmented controller is tested in a simulated environment first, and then deployed for outdoor field experiments. Results are shown in different scenarios using a cluster of three autonomous unmanned aerial vehicles.

scholarly journals Task Assignment for Multi-UAV under Severe Uncertainty by Using Stochastic Multicriteria Acceptability Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoxuan Hu ◽  
Jing Cheng ◽  
He Luo
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Task Assignment ◽  
Uncertain Information ◽  
Simulation Experiments ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Severe Uncertainty ◽  
Task Assignment Problem ◽  
Multi Uav ◽  
Assignment Approach

This paper considers a task assignment problem for multiple unmanned aerial vehicles (UAVs). The UAVs are set to perform attack tasks on a collection of ground targets in a severe uncertain environment. The UAVs have different attack capabilities and are located at different positions. Each UAV should be assigned an attack task before the mission starts. Due to uncertain information, many criteria values essential to task assignment were random or fuzzy, and the weights of criteria were not precisely known. In this study, a novel task assignment approach based on stochastic Multicriteria acceptability analysis (SMAA) method was proposed to address this problem. The uncertainties in the criteria were analyzed, and a task assignment procedure was designed. The results of simulation experiments show that the proposed approach is useful for finding a satisfactory assignment under severe uncertain circumstances.

scholarly journals Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wei Tan ◽  
Yong-jiang Hu ◽  
Yue-fei Zhao ◽  
Wen-guang Li ◽  
Xiao-meng Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Unmanned Aerial Vehicles ◽  
Voronoi Diagram ◽  
Pso Algorithm ◽  
Mission Planning ◽  
Cooperative System ◽  
Aerial Vehicles ◽  
Rendezvous Problem ◽  
Aerial Vehicle ◽  
Multi Uav

Unmanned aerial vehicles (UAVs) are increasingly used in different military missions. In this paper, we focus on the autonomous mission allocation and planning abilities for the UAV systems. Such abilities enable adaptation to more complex and dynamic mission environments. We first examine the mission planning of a single unmanned aerial vehicle. Based on that, we then investigate the multi-UAV cooperative system under the mission background of cooperative target destruction and show that it is a many-to-one rendezvous problem. A heterogeneous UAV cooperative mission planning model is then proposed where the mission background is generated based on the Voronoi diagram. We then adopt the tabu genetic algorithm (TGA) to obtain multi-UAV mission planning. The simulation results show that the single-UAV and multi-UAV mission planning can be effectively realized by the Voronoi diagram-TGA (V-TGA). It is also shown that the proposed algorithm improves the performance by 3% in comparison with the Voronoi diagram-particle swarm optimization (V-PSO) algorithm.

scholarly journals Overlap Avoidance of Mobility Models for Multi-UAVs Reconnaissance

2020 ◽  
Vol 10 (11) ◽  
pp. 4051 ◽  
Author(s):  
Yong-il Jo ◽  
Seonah Lee ◽  
Kyong Hoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Cooperative Work ◽  
The Other ◽  
Mobility Models ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Simulation Results

As avionics technologies have advanced, it is possible to perform many aerial applications which demand cooperative work with multiple Unmanned Aerial Vehicles (UAVs). Since one of the basic applications is reconnaissance, we focus on efficient cooperative reconnaissance. While random mobility models are useful for multi-UAVs reconnaissance, they suffer from overlapped reconnaissance problem that two or more UAVs reconnoiter a region at the same time. The overlapped reconnaissance also leads to imbalanced reconnaissance in which an area scanned by one UAV may be re-visited soon by the other UAV. Thus, we provide overlap avoidance schemes for the existing reconnaissance mobility models and enhance their performance. Throughout the simulations, we evaluate the effect of applying overlap avoidance in the existing models. The simulation results show that overlapped area is reduced by up to 20 times and 90%-coverage reaching time is improved by up to 19%.

scholarly journals A Distributed Approach for Collision Avoidance between Multirotor UAVs Following Planned Missions

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2404 ◽  
Author(s):  
Francisco Fabra ◽  
Willian Zamora ◽  
Julio Sangüesa ◽  
Carlos T. Calafate ◽  
Juan-Carlos Cano ◽  
...  
Keyword(s):  
Wireless Communications ◽  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Distributed Approach ◽  
Aerial Vehicles ◽  
Potential Applications ◽  
Simulation Results

As the number of potential applications for Unmanned Aerial Vehicles (UAVs) keeps rising steadily, the chances that these devices get close to each other during their flights also increases, causing concerns regarding potential collisions. This paper proposed the Mission Based Collision Avoidance Protocol (MBCAP), a novel UAV collision avoidance protocol applicable to all types of multicopters flying autonomously. It relies on wireless communications in order to detect nearby UAVs, and to negotiate the procedure to avoid any potential collision. Experimental and simulation results demonstrated the validity and effectiveness of the proposed solution, which typically introduces a small overhead in the range of 15 to 42 s for each risky situation successfully handled.

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